Delete utils

utils/data_loader.py

@@ -1,29 +0,0 @@
-# src/utils/data_loader.py
-
-import pandas as pd
-import json
-
-def load_restaurant_data(file_path: str) -> pd.DataFrame:
-    """
-    Load restaurant data from JSON file into a DataFrame.
-    
-    Args:
-        file_path (str): Path to the JSON file.
-    
-    Returns:
-        pd.DataFrame: DataFrame containing restaurant data.
-    """
-    with open(file_path, 'r', encoding='utf-8') as f:
-        data = json.load(f)
-    
-    df = pd.DataFrame(data)
-    # Create a text field for embedding and BM25
-    df['text'] = df.apply(
-        lambda row: f"{row['name']} ({row['cuisine']}): {', '.join(row['dishes'])}. "
-                    f"Price: {row['price_range']}, Distance: {row['distance']} km, "
-                    f"Rating: {row['rating']}. Description: {row['description']}",
-        axis=1
-    )
-    return df
-if __name__ == "__main__":
-    print(load_restaurant_data("./data/restaurants.json"))

utils/query_parser.py

@@ -1,76 +0,0 @@
-# src/utils/query_parser.py
-import pandas as pd
-import json
-from typing import Dict, Any
-from src.generation.llm import LLM
-
-class QueryParser:
-    def __init__(self, df: pd.DataFrame):
-        """
-        Initialize the query parser with restaurant data.
-        
-        Args:
-            df (pd.DataFrame): DataFrame containing restaurant data.
-        """
-        self.llm = LLM()
-        self.df = df
-        self.valid_cuisines = sorted(self.df['cuisine'].unique().tolist())
-        self.valid_price_ranges = sorted(self.df['price_range'].unique().tolist())
-        self.valid_dishes = sorted(set([dish for dishes in self.df['dishes'] for dish in dishes]))
-    
-    def parse_query(self, query: str) -> Dict[str, Any]:
-        """
-        Parse the query to extract features.
-        
-        Args:
-            query (str): User query.
-        
-        Returns:
-            Dict[str, Any]: Parsed features.
-        """
-        # Format prompt using LLM's prompt template
-        prompt = self.llm.format_query_prompt(
-            query=query,
-            cuisines=self.valid_cuisines,
-            dishes=self.valid_dishes,
-            price_ranges=self.valid_price_ranges
-        )
-        
-        # Generate response
-        response = self.llm.generate(prompt)
-        
-        # Parse JSON response
-        try:
-            json_start = response.find("{")
-            json_end = response.rfind("}") + 1
-            parsed = json.loads(response[json_start:json_end])
-            return parsed
-        except json.JSONDecodeError:
-            return {
-                "cuisine": None,
-                "menu": [],
-                "price_range": None,
-                "distance": None,
-                "rating": None,
-                "description": query
-            }
-
-
-# Quick test block for QueryParser
-if __name__ == "__main__":
-    import pandas as pd
-
-    sample_data = {
-        "cuisine": ["Italian", "Japanese"],
-        "price_range": ["$", "$$"],
-        "dishes": [["pizza", "pasta"], ["sushi", "ramen"]]
-    }
-    df = pd.DataFrame(sample_data)
-    parser = QueryParser(df)
-
-    user_query = "I want cheap sushi"
-    result = parser.parse_query(user_query)
-
-    print("Parsed Query Result:")
-    print(result)
-